Incremental models were constructed as follows: model 1, unadjusted; model 2, adjusted for age, sex, and ethnicity; model 3, additionally adjusted for BMI, HbA1c, diabetes duration, SBP, antihypertensive medications, total cholesterol, triglyceride, current smoking, and eGFR; and model 4, additionally adjusted for history of CVD.
A semi-analytical incremental model is developed which is suitable for any type of loading.
This paper addresses modeling causal relationships over event streams where data are unbounded and hence incremental modeling is required.
An incremental model was developed so as to predict the growth of fatigue cracks under complex load spectra.
An incremental model is derived to represent the considered system and an improved robust adaptive law is chosen to update the parameters of the linear adaptive controller.
Starting from a conventional complex formulation, an augmented incremental model is developed comprising both complex and real unknowns, corresponding to PQ and voltage-regulated buses respectively.
Thus, the incremental model is adopted in this paper.
The linear incremental model is shown in Fig. 10b, and the lateral value is almost constant.
Indeed, the most promising advantage of incremental model is its computational performance for optimizing gas network operations.
